matrix

问题 I save a matrix to a file like this: save(filepath, 'mtrx', '-ascii'); Is there a way to tell MATLAB to write 0 instead of 0.0000000e+000 values? It would be nice because it would be faster and easier to see which values differ from zero. 回答1: I suggest using DLMWRITE instead of SAVE since you're dealing with ASCII files. It will give you more control over the formatting. For example, you could create an output file delimited by spaces with a field width of 10 and 6 digits after the decimal

问题 I want to fill a matrix from an array of indices : import numpy as np indx = [[0,1,2],[1,2,4],[0,1,3],[2,3,4],[0,3,4]] x = np.zeros((5,5)) for i in range(5): x[i,indx[i]] = 1. The result is : array([[ 1., 1., 1., 0., 0.], [ 0., 1., 1., 0., 1.], [ 1., 1., 0., 1., 0.], [ 0., 0., 1., 1., 1.], [ 1., 0., 0., 1., 1.]]) As desired. Question Is there a way to do this in pure python/numpy without looping ? 回答1: Use advanced-indexing after intialization - x[np.arange(len(indx))[:,None], indx] = 1 来源：

问题 I've created a List of matrices, and now I want to get the maximum values of row in all matrices, how do I get them? Here is the code for the list: i <- 1 tryList <- list() treeList <- list() accList <- list() for(t_mtry in 1:40){ for(t_ntree in 20:300{ rf <- randomForest(class ~., data=training, mtry=t_mtry, ntree=t_ntree) tbl <- table(predicted = predict(rf,evalSet,type="class"),actual=evalSet$class) #get the accuracy of the classification as a list retVal <- accuracy(tbl) tryList <- c

问题 I'm using the following links to create a "Euclidean Similarity Matrix" (that I convert to a DataFrame). https://stats.stackexchange.com/questions/53068/euclidean-distance-score-and-similarity http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.distance.euclidean.html The way I'm doing it is an iterative approach which works but it takes a while when the datasets are big. The pandas pd.DataFrame.corr() is really fast and useful for pearson correlations. How can I perform

问题 I'm using the following links to create a "Euclidean Similarity Matrix" (that I convert to a DataFrame). https://stats.stackexchange.com/questions/53068/euclidean-distance-score-and-similarity http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.distance.euclidean.html The way I'm doing it is an iterative approach which works but it takes a while when the datasets are big. The pandas pd.DataFrame.corr() is really fast and useful for pearson correlations. How can I perform

问题 I'm using the following links to create a "Euclidean Similarity Matrix" (that I convert to a DataFrame). https://stats.stackexchange.com/questions/53068/euclidean-distance-score-and-similarity http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.distance.euclidean.html The way I'm doing it is an iterative approach which works but it takes a while when the datasets are big. The pandas pd.DataFrame.corr() is really fast and useful for pearson correlations. How can I perform

问题 I am attempting to project a series of 3D points onto the screen using a perspective camera matrix. I do not have world space (or consider it being an identity matrix) and my camera does not have camera space (or consider it an identity matrix), I do have a 4x4 matrix for my object space. I am taking the object matrix and multiplying it by the camera perspective matrix, generated with the following method: Matrix4 createPerspectiveMatrix( Float fov, Float aspect, Float near, Float far ) {

问题 Suppose I have a matrix A of dimension Nx(N-1) in MATLAB, e.g. N=5; A=[1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16; 17 18 19 20 ]; I want to transform A into an NxN matrix B , just by adding a zero diagonal, i.e., B=[ 0 1 2 3 4; 5 0 6 7 8; 9 10 0 11 12; 13 14 15 0 16; 17 18 19 20 0]; This code does what I want: B_temp = zeros(N,N); B_temp(1,:) = [0 A(1,:)]; B_temp(N,:) = [A(N,:) 0]; for j=2:N-1 B_temp(j,:)= [A(j,1:j-1) 0 A(j,j:end)]; end B = B_temp; Could you suggest an efficient way to

问题 I have three matrices, each of size 4x1 . I want to copy all of these matrices to another matrix of size 4x3 and call it R . Is there a smart way to do it? 回答1: You can just use hconcat for horizontal concatenation. You can use it per matrix, e.g. hconcat( mat1, mat2, R ), or apply it directly on a vector or array of matrices. Here's a sample code: vector<Mat> matrices = { Mat(4, 1, CV_8UC1, Scalar(1)), Mat(4, 1, CV_8UC1, Scalar(2)), Mat(4, 1, CV_8UC1, Scalar(3)), }; Mat R; hconcat( matrices,

问题 Ok guys, I am using the following library: http://www.codeproject.com/KB/recipes/AdvancedMatrixLibrary.aspx And I wish to calculate the eigenvectors of certain matrices I have. I do not know how to formulate the code. So far I have attempted: Matrix MatrixName = new Matrix(n, n); Matrix vector = new Matrix(n, 0); Matrix values = new Matrix(n, 0); Matrix.Eigen(MatrixName[n, n], values, vector); However it says that the best overloaded method match has some invalid arguments. I know the library